code: def libra2dgl_build_adjlist(
      feat,
      gfeat,
      adj,
      inner_node,
      ldt,
      gdt_key,
      gdt_value,
      node_map,
      lr,
      lrtensor,
      num_nodes,
      nc,
      c,
      feat_size,
      labels,
      trainm,
      testm,
      valm,
      glabels,
      gtrainm,
      gtestm,
      gvalm,
      feat_shape,
  ):
      """
      This function invokes C/C++ code for pre-processing Libra output.
      After graph partitioning using Libra, once the local and global dictionaries are built,
      for each node in each partition, this function copies the split node details from the
      global dictionary. It also copies features, label, train, test, and validation information
      for each node from the input graph to the corresponding partitions.
      Parameter details are present in dgl/src/array/libra_partition.cc
      """
      _CAPI_DGLLibra2dglBuildAdjlist(
          to_dgl_nd(feat),
          to_dgl_nd_for_write(gfeat),
          to_dgl_nd_for_write(adj),
          to_dgl_nd_for_write(inner_node),
          to_dgl_nd(ldt),
          to_dgl_nd(gdt_key),
          to_dgl_nd(gdt_value),
          to_dgl_nd(node_map),
          to_dgl_nd_for_write(lr),
          to_dgl_nd(lrtensor),
          num_nodes,
          nc,
          c,
          feat_size,
          to_dgl_nd(labels),
          to_dgl_nd(trainm),
          to_dgl_nd(testm),
          to_dgl_nd(valm),
          to_dgl_nd_for_write(glabels),
          to_dgl_nd_for_write(gtrainm),
          to_dgl_nd_for_write(gtestm),
          to_dgl_nd_for_write(gvalm),
          feat_shape,
      )
  
imports: from __future__ import absolute_import
  from .None import backend, ndarray
  from ._ffi.function import _init_api
  from .base import DGLError
label_desc: Use image node_id 24 for calling a global function with example usage: libra2dgl_build_adjlist(feat, gfeat, adj, inner_node, ldt, gdt_key, gdt_value, node_map, lr, lrtensor, num_nodes, nc, c, feat_size, labels, trainm, testm, valm, glabels, gtrainm, gtestm, gvalm, feat_shape) without return types